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package br.com.mailanalyzer.analise2;

/**
Mr. Gilleland,

As you may know, the Apache Jakarta Commons project had appropriated
your sample implementation of the Levenshtein Distance algorithm for
its commons-lang Java library.  While attempting to use it with two
very large strings, I encountered an OutOfMemoryError, due to the fact
that a matrix is created with the dimensions of the two strings'
lengths.  I know you created the implementation to go with your
(excellent) illustration of the algorithm, so this matrix approach
translates that illustration and tutorial perfectly.

However, as I said, the matrix approach doesn't lend itself to getting
the edit distance of two large strings.  For this purpose, I modified
your implementation to use two single-dimensional arrays; this is
clearly more memory-friendly (although it probably results in some very
slight performance degradation when comparing smaller strings).

I've submitted the modification to the maintainers of the commons-lang
project, and I've appended the relevant method below.

Thanks!

Chas Emerick

 */

/*
The difference between this impl. and the previous is that, rather
than creating and retaining a matrix of size s.length()+1 by t.length()+1,
we maintain two single-dimensional arrays of length s.length()+1.  The first, d,
is the 'current working' distance array that maintains the newest distance cost
counts as we iterate through the characters of String s.  Each time we increment
the index of String t we are comparing, d is copied to p, the second int[].  Doing so
allows us to retain the previous cost counts as required by the algorithm (taking
the minimum of the cost count to the left, up one, and diagonally up and to the left
of the current cost count being calculated).  (Note that the arrays aren't really
copied anymore, just switched...this is clearly much better than cloning an array
or doing a System.arraycopy() each time  through the outer loop.)

Effectively, the difference between the two implementations is this one does not
cause an out of memory condition when calculating the LD over two very large strings.
 */
public class Levenshtein {

    public static int getLevenshteinDistance(String s, String t) {
        if (s == null || t == null) {
            throw new IllegalArgumentException("Strings must not be null");
        }
        int n = s.length(); // length of s
        int m = t.length(); // length of t
        if (n == 0)return m;
        if (m == 0)return n;
        int p[] = new int[n + 1];//previous' cost array, horizontally
        int d[] = new int[n + 1];// cost array, horizontally
        int _d[]; //placeholder to assist in swapping p and d
        // indexes into strings s and t
        int i; // iterates through s
        int j; // iterates through t
        char t_j; // jth character of t
        int cost; // cost
        for (i = 0; i <= n; i++)p[i] = i;

        for (j = 1; j <= m; j++) {
            t_j = t.charAt(j - 1);
            d[0] = j;
            for (i = 1; i <= n; i++) {
                cost = s.charAt(i - 1) == t_j ? 0 : 1;
                // minimum of cell to the left+1, to the top+1, diagonally left and up +cost
                d[i] = Math.min(Math.min(d[i - 1] + 1, p[i] + 1), p[i - 1] + cost);
            }
            // copy current distance counts to 'previous row' distance counts
            _d = p;
            p = d;
            d = _d;
        }

        // our last action in the above loop was to switch d and p, so p now
        // actually has the most recent cost counts
        return p[n];
    }
    /**
     * Valor padrao da porccentagem: 30%
     */
    public static final int PORCENTAGEM_PADRAO = 30;

    private static int getPorcentagem(double p, String s){
        return (int)(s.length()*p/100);
    }

    public static synchronized boolean EQUIDISTANT(String a, String b){
        String menor = (a.length() < b.length())?a:b;
        return getPorcentagem(PORCENTAGEM_PADRAO, menor)<= getLevenshteinDistance(a, b)?true:false;
    }
}
